A model-following adaptive controller using radial basis function networks

Abstract

In this paper, we propose a method to design a model-following adaptive controller using radial basis function networks (RBF-NNs). The method is very simple to implement by exploiting the property of RBF-NNs. The propased method identifies linear or nonlinear plants and implements a stable model-following adaptive controller by utilizing identification results. Simulation results show the effectiveness of the proposed control schemes. Keywords linear and nonlinear plants, neural networks, radial basis function networks